78c4e3710d
### What changes were proposed in this pull request?
This PR modifies `DecorrelateInnerQuery` to handle the COUNT bug for lateral subqueries. Similar to SPARK-15370, rewriting lateral subqueries as joins can change the semantics of the subquery and lead to incorrect answers.
However we can't reuse the existing code to handle the count bug for correlated scalar subqueries because it assumes the subquery to have a specific shape (either with Filter + Aggregate or Aggregate as the root node). Instead, this PR proposes a more generic way to handle the COUNT bug. If an Aggregate is subject to the COUNT bug, we insert a left outer domain join between the outer query and the aggregate with a `alwaysTrue` marker and rewrite the final result conditioning on the marker. For example:
```sql
-- t1: [(0, 1), (1, 2)]
-- t2: [(0, 2), (0, 3)]
select * from t1 left outer join lateral (select count(*) from t2 where t2.c1 = t1.c1)
```
Without count bug handling, the query plan is
```
Project [c1#44, c2#45, count(1)#53L]
+- Join LeftOuter, (c1#48 = c1#44)
:- LocalRelation [c1#44, c2#45]
+- Aggregate [c1#48], [count(1) AS count(1)#53L, c1#48]
+- LocalRelation [c1#48]
```
and the answer is wrong:
```
+---+---+--------+
|c1 |c2 |count(1)|
+---+---+--------+
|0 |1 |2 |
|1 |2 |null |
+---+---+--------+
```
With the count bug handling:
```
Project [c1#1, c2#2, count(1)#10L]
+- Join LeftOuter, (c1#34 <=> c1#1)
:- LocalRelation [c1#1, c2#2]
+- Project [if (isnull(alwaysTrue#32)) 0 else count(1)#33L AS count(1)#10L, c1#34]
+- Join LeftOuter, (c1#5 = c1#34)
:- Aggregate [c1#1], [c1#1 AS c1#34]
: +- LocalRelation [c1#1]
+- Aggregate [c1#5], [count(1) AS count(1)#33L, c1#5, true AS alwaysTrue#32]
+- LocalRelation [c1#5]
```
and we have the correct answer:
```
+---+---+--------+
|c1 |c2 |count(1)|
+---+---+--------+
|0 |1 |2 |
|1 |2 |0 |
+---+---+--------+
```
### Why are the changes needed?
Fix a correctness bug with lateral join rewrite.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added SQL query tests. The results are consistent with Postgres' results.
Closes #33070 from allisonwang-db/spark-35551-lateral-count-bug.
Authored-by: allisonwang-db <allison.wang@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
(cherry picked from commit
|
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|---|---|---|
| .. | ||
| catalyst | ||
| core | ||
| hive | ||
| hive-thriftserver | ||
| create-docs.sh | ||
| gen-sql-api-docs.py | ||
| gen-sql-config-docs.py | ||
| gen-sql-functions-docs.py | ||
| mkdocs.yml | ||
| README.md | ||
Spark SQL
This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.
Spark SQL is broken up into four subprojects:
- Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
- Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
- Hive Support (sql/hive) - Includes extensions that allow users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow users to run queries that include Hive UDFs, UDAFs, and UDTFs.
- HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.
Running ./sql/create-docs.sh generates SQL documentation for built-in functions under sql/site, and SQL configuration documentation that gets included as part of configuration.md in the main docs directory.